Abstract: To improve aircraft assembly efficiency and personnel utilization,a multi-objective and multi-constrained model of the type-E aircraft pulsating assembly line balancing problem was constructed according to the characteristics of aircraft pulsating assembly line,and a hybrid algorithm which combined Non-dominated Sorting Genetic Algorithm (NSGA),cuckoo search algorithm and dynamic search algorithm was designed to solve the problem.The dynamic search algorithm solved the low efficiency and poor quality of the solution to type-E assembly line balancing problem;the NSGA raised the optimization effect of assembly sequence by improving the individual distance calculation method;the cuckoo search algorithm improved Lévy flight distance calculation equation to search the optimal station number.The algorithm was proved to be senior to that in the related research,and the validity of the model was verified by the application example.

Key words: aircraft pulsating assembly line, balancing optimization, non-dominated sorting genetic algorithm, cuckoo search algorithm, dynamic search algorithm, type-E assembly line balancing problem

摘要： 为提高飞机装配效率和人员利用率,根据飞机总装脉动生产线的特点和平衡优化需求,构建多目标多约束的E类飞机总装脉动生产线平衡问题模型,并设计一种结合非支配排序遗传算法、布谷鸟搜索算法和动态搜索算法的混合优化算法进行求解。其中动态搜索算法解决E类装配线平衡问题求解效率低下以及质量不佳的问题;非支配排序遗传算法通过改进个体距离计算方法提高装配序列的优化效果;布谷鸟搜索算法则借助改进莱维飞行距离计算式提高最优站位数量的搜索能力。最后通过基准问题测试证明算法的性能优于相关问题算法,并借助应用实例验证了模型的有效性。

关键词: 飞机总装脉动生产线, 平衡优化, 非支配排序遗传算法, 布谷鸟搜索算法, 动态搜索算法, E类装配线平衡问题